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Security Advisories: GSA_kwCzR0hTQS1qcTZ4LTk5aGotcTYzNs4AAv-s

Seg fault in `ndarray_tensor_bridge` due to zero and large inputs

Impact

If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. E.g. the following raises an error:

np.ones((0, 2**31, 2**31))

An example of a proof of concept:

import numpy as np
import tensorflow as tf

input_val = tf.constant([1])
shape_val = np.array([i for i in range(21)])

tf.broadcast_to(input=input_val,shape=shape_val)

The return value of PyArray_SimpleNewFromData, which returns null on such shapes, is not checked.

Patches

We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784.

The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Pattarakrit Rattanukul.

Permalink: https://github.com/advisories/GHSA-jq6x-99hj-q636
JSON: https://advisories.ecosyste.ms/api/v1/advisories/GSA_kwCzR0hTQS1qcTZ4LTk5aGotcTYzNs4AAv-s
Source: GitHub Advisory Database
Origin: Unspecified
Severity: Moderate
Classification: General
Published: over 1 year ago
Updated: about 1 year ago


CVSS Score: 4.8
CVSS vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H

Identifiers: GHSA-jq6x-99hj-q636, CVE-2022-41884
References: Repository: https://github.com/tensorflow/tensorflow

Affected Packages

pypi:tensorflow-gpu
Dependent packages: 146
Dependent repositories: 11,499
Downloads: 354,170 last month
Affected Version Ranges: >= 2.10.0, < 2.10.1, >= 2.9.0, < 2.9.3, < 2.8.4
Fixed in: 2.10.1, 2.9.3, 2.8.4
All affected versions: 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.7.0, 1.7.1, 1.8.0, 1.9.0, 1.10.0, 1.10.1, 1.11.0, 1.12.0, 1.12.2, 1.12.3, 1.13.1, 1.13.2, 1.14.0, 1.15.0, 1.15.2, 1.15.3, 1.15.4, 1.15.5, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.0, 2.8.1, 2.8.2, 2.8.3, 2.9.0, 2.9.1, 2.9.2, 2.10.0
All unaffected versions: 2.8.4, 2.9.3, 2.10.1, 2.11.0, 2.12.0
pypi:tensorflow-cpu
Dependent packages: 71
Dependent repositories: 2,483
Downloads: 1,005,140 last month
Affected Version Ranges: >= 2.10.0, < 2.10.1, >= 2.9.0, < 2.9.3, < 2.8.4
Fixed in: 2.10.1, 2.9.3, 2.8.4
All affected versions: 1.15.0, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.0, 2.8.1, 2.8.2, 2.8.3, 2.9.0, 2.9.1, 2.9.2, 2.10.0
All unaffected versions: 2.8.4, 2.9.3, 2.10.1, 2.11.0, 2.11.1, 2.12.0, 2.12.1, 2.13.0, 2.13.1, 2.14.0, 2.14.1, 2.15.0, 2.15.1, 2.16.1
pypi:tensorflow
Dependent packages: 1,733
Dependent repositories: 73,755
Downloads: 21,673,933 last month
Affected Version Ranges: >= 2.10.0, < 2.10.1, >= 2.9.0, < 2.9.3, < 2.8.4
Fixed in: 2.10.1, 2.9.3, 2.8.4
All affected versions: 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.7.0, 1.7.1, 1.8.0, 1.9.0, 1.10.0, 1.10.1, 1.11.0, 1.12.0, 1.12.2, 1.12.3, 1.13.1, 1.13.2, 1.14.0, 1.15.0, 1.15.2, 1.15.3, 1.15.4, 1.15.5, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.0, 2.8.1, 2.8.2, 2.8.3, 2.9.0, 2.9.1, 2.9.2, 2.10.0
All unaffected versions: 2.8.4, 2.9.3, 2.10.1, 2.11.0, 2.11.1, 2.12.0, 2.12.1, 2.13.0, 2.13.1, 2.14.0, 2.14.1, 2.15.0, 2.15.1, 2.16.1